Debris flows are among the most destructive natural hazards in mountainous areas, and climate change is expected to increase their frequency and intensity. The RESFLOW project aims to enhance monitoring and prediction of these hazards using a data-driven, integrated approach.
RESFLOW combines Earth Observation (EO) data, artificial intelligence (AI), climate models, Dynamic Vegetation Models, and real-time meteorological information to improve hazard assessments, early warning systems, and disaster preparedness. High-resolution digital elevation models, soil and vegetation data, and climate inputs feed a dynamic debris flow model, continuously updated with satellite observations from Sentinel-1, Sentinel-2, Landsat, and NASA IMERG.
High-quality, harmonized data is essential to facilitate continuous monitoring and development of advanced landslide detection techniques. As part of a EUREKA consortium, together with partners GGIT, AFAD, ITU and Meteoclim, GeoVille is responsible for harmonizing EO, land cover, and meteorological datasets, and for developing debris flow identification processing chains using multi-mission satellite data. Implementing regional climate projections will also allow assessment of debris flow risks under future scenarios.
Beyond technology, RESFLOW emphasizes capacity building and public awareness, providing authorities and communities with tools and knowledge to interpret hazard information. Combining harmonized data, advanced modeling, and AI, RESFLOW delivers actionable insights to strengthen disaster preparedness and resilience in vulnerable areas, demonstrating how modern technology can transform hazard monitoring into timely and actionable information for decision-makers and communities.
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